HOTFLoc++: End-to-End Hierarchical LiDAR Place Recognition, Re-Ranking, and 6-DoF Metric Localisation in Forests

arXiv — cs.CV•Thursday, November 13, 2025 at 5:00:00 AM

HOTFLoc++ represents a significant leap in LiDAR technology, offering an end-to-end solution for place recognition and localization in challenging forest environments. By utilizing an octree-based transformer, the framework effectively extracts hierarchical local descriptors, which enhances its robustness to clutter and viewpoint variations. The introduction of a learnable multi-scale geometric verification module further minimizes re-ranking failures, leading to a remarkable Recall@1 of 90.7% on the CS-Wild-Places dataset, an improvement of 29.6 percentage points over previous baselines. Additionally, HOTFLoc++ demonstrates runtime improvements of two orders of magnitude compared to RANSAC for dense point clouds, making it a highly efficient tool for real-time applications. With an impressive average Recall@1 of 91.7% on Wild-Places and 96.0% on MulRan, the framework not only excels in forest settings but also maintains high performance across various benchmarks. This advancement is p…

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